A custom ML model trained on your own customer data. Outputs a churn probability per customer, surfaces the specific risk signals for your business, and integrates with your CRM so your retention team can act in time.
We pick the best-fit components based on your data volume, latency needs, and privacy requirements.
At least 12 months of customer activity with churn events labeled. 24+ months is better — it lets the model account for seasonality. We'll audit your data quality before committing to a build.
Depends on your data richness and definition of churn. For SaaS clients with usage + billing + support data, we typically see 82-89% ROC-AUC. For simpler datasets it's lower but still much better than heuristics.
Standard cadence is weekly, but we can set daily or event-triggered depending on your churn definition. The retraining pipeline is automated — you don't manage it.
Salesforce, HubSpot, Zoho, Zendesk, Intercom, custom CRMs via webhook. We push the probability score and top-3 risk signals into a custom field on the customer record.
Yes. We deploy on your cloud (AWS/GCP/Azure), monitor drift, and alert if accuracy drops. Optional retainer for ongoing tuning.
Visualize the churn scores across your customer base.
Explore →Auto-trigger retention workflows for high-risk customers.
Explore →Run the model on your own hardware for sensitive customer data.
Explore →Bring us three canceled customers — we'll show you what the model would have flagged, how early, and why. Diagnostic call is 30 minutes and free.
